JP3227958B2 - Life activity current source estimation method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for estimating the position, orientation, and size of a biological activity current source, and more particularly to a method for estimating a biological activity current source using a minimum norm method.

[0002]

2. Description of the Related Art When a living body is stimulated, the polarization formed across a cell membrane is broken and a living activity current flows. This biological activity current appears in the brain and heart, and is recorded as an electroencephalogram and an electrocardiogram. The magnetic field generated by the biological activity current is recorded as a magnetoencephalogram and a magnetocardiogram.

Recently, as a device for measuring a minute magnetic field in a living body, SQUID (Superconducting Quantum Inter
face Device: A sensor using a superconducting quantum interferometer) has been developed. This sensor is placed outside the head, and the sensor can non-invasively measure a small magnetic field generated by a current dipole (hereinafter simply referred to as a current source), which is a biological activity current source, generated in the brain. From the measured magnetic field data, the position, direction, and size of the current source related to the lesion are estimated, and the estimated current source is displayed on a tomographic image obtained by an X-ray CT or MRI device, and the physics of the affected part is displayed. It is used to identify the target position.

Conventionally, as one of current source estimation methods, there is a method using a minimum norm method (for example, WHKullman
n, KDJandt, K. Rehm, HASchlitt, WJDallas and
WESmith, Advances in Biomagnetism, pp.571-574, P
lenum Pless, New York, 1989).

A conventional current source estimation method using the minimum norm method will be described below with reference to FIG. As shown in FIG. 8, a multi-channel SQUID sensor 1 is provided near the subject M. Multichannel SQUID sensor 1 is accommodated by immersing a number of magnetic sensors (pickup coil) S ₁ to S _m in the refrigerant such as liquid nitrogen in a container called a dewar.

On the other hand, a large number of grid points (1) to (n) are set three-dimensionally in, for example, the brain, which is a diagnosis target area of the subject M, and an unknown current source (current dipole) is set at each grid point. Assuming that each current source is represented by a three-dimensional vector VP _j (j = 1 to n). Then, the magnetic field B _i .about.B _m detected by the magnetic sensor S ₁ to S _m of the SQUID sensor 1 is expressed by the following equation (1).

[0007]

(Equation 1)

In equation (1), VP _j = (P _jx , P _jy , P _jz ) α _ij = (α _ijx, α _ijy, α _ijz ). Note that α _ij is the magnetic sensors S ₁ to S ₁ when a current source having a unit size in the X, Y, and Z directions is placed on a grid point.
Is a known coefficient which represents the strength of the magnetic field detected by each position of the S _m.

[B] = (B ₁ , B ₂ ,..., B _m ) [P] = (P _1x , P _1y , P _1z , P _2x , P _2y , P _{2z ,.}
(P _nx , P _ny , P _nz ), the expression (1) can be rewritten into a linear relational expression like the expression (2). [B] = A [P] (2)

In the equation (2), A is a matrix having 3n × m elements represented by the following equation (3).

[0011]

(Equation 2)

Here, when the inverse matrix of A is represented by A ⁻ ,
[P] is represented by the following equation (4). (P) = A ^- (B) ......... (4)

The simultaneous equation represented by the equation (4) is obtained by comparing the number m of equations (the number of magnetic sensors S _{1 to} S _m , for example, several 10 to several hundred) with the number n of unknowns (for each grid point). Since the number of assumed current sources is, for example, several hundred to several thousand), no solution is obtained. Therefore, a condition is added to minimize the norm | [P] | of the vector [P]. Then, the above equation (4) is expressed as the following equation (5). [P] = A ⁺ [B] (5) where A ⁺ is a generalized inverse matrix expressed by the following equation (6). ^{A + = A t (AA t} ) -1 ......... (6) However, A ^t is the transpose matrix of A.

By solving the above equation (5), the current sources VP _j on each grid point
Are estimated, and the one having the largest value among them is assumed to be close to the true current source. This is the principle of the current source estimation method using the minimum norm method.

However, in the above-mentioned minimum norm method, since current sources are assumed at all positions where the grid points are arranged, the degree of freedom of the solution increases spatially, which may cause an erroneous solution to be obtained. I have.

Therefore, based on the assumption that the magnetic field source is composed of current sources existing in several local regions, grid points having a low possibility of having a solution are gathered near higher grid points to obtain a space. The present inventors have proposed a method of obtaining a solution that is closer to the true solution by lowering the degree of freedom of the solution by adding a general constraint (hereinafter referred to as a lattice point moving minimum norm method) (Tomita) Sada, Shigeki Kajiwara, Yasushi Kondo, Keiichi Yoshida, Shinji Yamamoto, Takashi Otsu, Naoichi Yakimaki, Hisashi Kato: Transactions of the 8th Annual Meeting of the Japanese Society of Biomagnetism, Vol. 6, pp. 86-89, 1993
). Hereinafter, the grid point moving minimum norm method will be described.

In the grid point moving minimum norm method, the probability that a solution exists on the j-th grid point is expressed by the following equation (7).

[0018]

(Equation 3)

In the above equation (7), Vr _j and VP _j are the position vector of the j-th grid point and the minimum norm solution on the grid point, and n is the number of grid points. The first term of equation (7) represents the intensity of the current source on the grid point, and the second term represents the density of the current source near the grid point. Further, β and γ are empirical parameters, and are appropriately determined based on, for example, an isomagnetic field map created from data obtained by the above-described magnetic sensors. The second term of equation (7) is that if the individual current sources have small intensities but a large number are dense, those lattice points will be replaced by other lattice points with low density but strong individual intensities. Added to avoid subordination. formula
The higher the accuracy given by (7), the higher the possibility that a solution exists near that grid point.

Next, another grid point is moved to a position near a grid point having a large value of the equation (7). However, there is a possibility that the current source is located at a plurality of positions or is spread spatially. There is also. So, we divide the grid points into several groups,
Move the grid points within each group. In order to group each grid point, a group function represented by the following equation (8) is used.

[0021]

(Equation 4)

The above equation (8) represents the degree of influence of the j-th grid point on the i-th grid point. α is a parameter that determines the shape of the function of equation (8), and is appropriately set empirically, for example, similarly to β and γ described above.

FIG. 9 shows an example in which grid points are grouped. In the figure, the horizontal axis is a position vector of a grid point, the vertical axis is a group function, A, B, and C are grid points, φ _A , φ
_B and φ _C are group functions of the lattice points A, B and C.
When the lattice point B has the largest influence on the lattice point A, the lattice point A is assumed to be subordinate to the lattice point B. Therefore, grid points A and B belong to the same group. on the other hand,
Since the lattice point C itself has the greatest influence on the lattice point C, the lattice point C belongs to a different group from the lattice points A and B. In this way, the grid point group is divided into multiple single groups.

After the grid points are divided into groups, the other grid points belonging to the same group are moved to the grid point having the highest probability of existence in each group, and the minimum norm solution is obtained again.
The moving distance of each lattice point at this time is a very small distance, and is determined by, for example, applying a predetermined coefficient to the distance between each lattice point. By repeating the above operation, the solution is made to converge on some local regions.

The principle of the grid point moving minimum norm method has been described above. FIGS. 10 and 11 schematically show how grid points are grouped. In FIG. 10, N is a lattice point group initially set, and N ₁ and N ₂ are new lattice point groups obtained by moving the lattice point group N in groups. N ₃ , N ₄ , N ₅ , and N ₆ , N ₇ in FIG. 11 are grid point groups obtained based on further grouping the grid point groups N ₁ , N ₂ .

[0026]

Although the grid point moving minimum norm method is excellent in that a solution closer to a true solution can be obtained, the following new problem has been clarified. .

That is, in the grid point moving minimum norm method,
The parameters α, β, and γ need to be appropriately set empirically. These parameters are the location of the current source,
Since it depends on the size, direction, etc., it is not easy for an inexperienced operator to appropriately set the values of the respective parameters using the isomagnetic field map as described above. Incorrect settings can result in results that deviate from the true solution.

The present invention has been made in view of such circumstances, and among the above-mentioned parameters α, β, γ, in particular, parameters β, β related to the accuracy of existence of a solution on each grid point. It is an object of the present invention to provide a life activity current source estimation method that can easily and accurately estimate a current source without setting γ.

[0029]

Means for Solving the Problems In order to solve the above problems, as a result of intensive studies by the present inventors, three orthogonal components of a magnetic field generated by a current source in a living body are simultaneously measured (vector measurement). If the above grid point moving minimum norm method is applied using this data, the current can also be calculated by the following equation (9) in which the parameter γ in equation (7) is set to 0 (thus, setting of the parameter β is unnecessary). It has been found that the source can be estimated correctly. Q (Vr _j ) = | VP _j | ……… (9)

The reason why the current source can be correctly estimated by the equation (9) that does not include the second term of the equation (7) is considered as follows. Generally, each magnetic sensor for detecting a magnetic field generated by a current source in a living body has a coil axis of each magnetic sensor S, as shown in FIG. It is pointed and arranged. In each magnetic sensor S, as shown in FIG. 12B, a pair of coils L ₁ and L ₂ are provided in the radial direction of the sphere (Z in FIG. 12B).
Direction), the detected magnetic field data is Z
Only the directional component. That is, since a magnetic field having components in three orthogonal directions X, Y, and Z is detected only in the Z direction, the detected magnetic field data has low mutual independence and low spatial resolution. Met. Result, expression
It is considered that the second term of (7), that is, the influence of the density of the current source near the lattice point on the existence probability Q of the solution on each lattice point was large.

On the other hand, when the magnetic field generated by the current source of the living body is vector-measured, three orthogonal magnetic fields from the subject are obtained.
Since the directional components X, Y, and Z are detected, the independence between the measured magnetic field data is increased, and as a result, the spatial resolution is improved. Therefore, even without considering the second term of equation (7),
It is considered that the existence probability Q of the solution on each grid point can be accurately obtained by only the first term.

The present invention based on the above findings has the following configuration. That is, the present invention
A large number of grid points are set in the subject when estimating the physical quantity including any of the position, size, and direction of the biological activity current source from data obtained by detecting the magnetic field generated by the biological activity current with multiple magnetic sensors Then, the relational expression between the unknown current source on each grid point and the magnetic field data measured by each magnetic sensor is added with a condition that the norm of a vector having the current source at each grid point as an element is minimized. In the biological activity current source estimation method using the method (minimum norm method) to determine the physical quantity of each current source by solving
(A) A large number of grid points are set in a subject, and an unknown current source on each grid point and three orthogonal components of a magnetic field generated by a biological activity current are detected simultaneously by a plurality of magnetic sensors. A first step of solving a relational expression with the obtained magnetic field data of three orthogonal components by the minimum norm method to obtain a current source on each grid point; and (b) each grid point obtained in the first step. A second step of determining the accuracy of the presence of the current source at each grid point according to the size (intensity) of the current source of (c), and (c) determining the grid point group based on the accuracy determined in the second step. A third step of dividing into a plurality of groups, and (d) moving another lattice point near a lattice point where a current source having a maximum size exists in each of the divided lattice point groups. A fourth step of rearranging the point group, and (e) a step of rearranging the points on each of the rearranged grid points. Source is those and a fifth process of obtaining by using the minimum norm method.

[0033]

The operation of the present invention is as follows. The current source estimated in the first step is not a true current source, but a current source close thereto. Therefore, if another grid point group is moved to the vicinity of the grid point where the estimated current source is located, the appropriate grid point arrangement is reconstructed and the minimum norm solution is obtained, without increasing the number of grid points. In addition, the estimation accuracy of the current source can be improved. However, when there are a plurality of true current sources, it is important to determine which grid point is closer to each grid point. Therefore, in the second process, the accuracy of the existence of the current source at each grid point is determined. At this time, since the magnetic field data detected by each magnetic sensor is magnetic field data of three orthogonal components, the accuracy of the existence of the current source at each grid point is determined based only on the size of the current source at each grid point. Desired. In the third step, the second
The group of grid points is divided into a plurality of groups based on the accuracy obtained in the process. Then, in the fourth process, for each of the divided grid point groups, another grid point is moved to the vicinity of the grid point where the current source having the maximum size exists. In the fifth step, a current source on each of the rearranged grid points is obtained by the minimum norm method. By repeatedly performing the above processing, even if there are a plurality of true current sources, each current source is accurately estimated.

[0034]

An embodiment of the present invention will be described below with reference to the flowchart of FIG.

First, as described with reference to FIG.
The orthogonal three-directional components of the minute magnetic field from the subject M are simultaneously measured (vector measurement) by the multi-channel SQID sensor 1 disposed in close proximity to (step S1).
However, the magnetic sensors (pickup coils) S _{1 to} S _{m of the} multi-channel SQID sensor 1 used here.
Is composed of three pickup coils each having detection sensitivity in three orthogonal directions. As this type of pickup coil, for example, there is a triaxial gradiometer. In the gradiometer, the pickup coil is divided into two oppositely wound coils, thereby canceling a uniform magnetic field and detecting only a magnetic field having a gradient.

FIG. 2 schematically shows the configuration of a three-axis gradiometer. The pickup coils L _X , L _Y , L _Z are:
The magnetic field components in the X, Y, and Z directions are detected. The configuration of the triaxial gradiometer is not particularly limited. For example, a triaxial gradiometer having a triaxial coil mounted so as to be orthogonal to six surfaces of a cubic core material, and Japanese Unexamined Patent Publication No. Hei.
No. 1, the low temperature resistant flexible material is wound in a cylindrical shape, and the flexible material is interconnected on the surface of the flexible material at a predetermined width in parallel with each other and in reverse winding. The superconducting thin-film coil pairs are set at different angles from each other.
A triaxial gradiometer or the like formed as a pair is used.

Next, similarly to the conventional example shown in FIG. 8, a three-dimensional grid point group N is set evenly in, for example, the brain, which is a diagnostic symmetric region (step S2).

Then, using the minimum norm method described above,
A current source (minimum norm solution) at each grid point is obtained (step S3).

Next, the accuracy of the existence of the current source on each grid point is determined by the above-mentioned equation (9) (step S4).

Then, in order to move a grid point having a small degree of accuracy to a position near a grid point having a higher degree of certainty, the above equation is used.
Using the group function φ defined in (8), each grid point group N
Are grouped (step S5). The parameter (movement parameter) α in the equation (8) is empirically set to an appropriate value as described above. Preferably, the optimum movement parameter α can be set by a method described later.

Next, in each group, the other grid points in each group are moved by a small distance near the grid point having the maximum function value (the size of the current source) (step S).
6, see FIG. 10). The method for moving the lattice points is not particularly limited, but as described above, a method for setting a new lattice point distance by multiplying the distance between lattice points by an appropriately set coefficient, Considering the magnitude of the current source at a point as mass, and assuming that gravity acts on each grid point by gravity,
There is a method of calculating the moving distance of each grid point.

In the next step S7, the divided grid point group (N ₁ , N _{2 in} FIG. 10) obtained by moving in step S6
In, it is determined whether the minimum grid point interval is equal to or smaller than a predetermined interval. This interval is appropriately determined according to the estimated position accuracy of the current source.

At the first stage of the grape division, since the moving distance of each grid point is appropriately set so that the minimum grid point interval is equal to or larger than a predetermined value, the process returns to step S3.
Then, the divided grid point groups N ₁ and N ₂ are regarded as one new grid point group, and the current source of each rearranged grid point is obtained by the minimum norm method. When the current source is obtained for each of the grid points of the divided grid point groups N ₁ and N ₂ , as in the previous case, for each of the divided grid point groups N ₁ and N ₂ , the accuracy of the existence of the current source on each grid point is determined. (Step S4), and the divided grid point groups N ₁ and N ₂ are further divided into groups (Step S4).
5). Then, moving the grid points in each group (step S6), and a new division grid point group (N ₃ of FIG. 11 to
Obtain the N _7).

The above processing is repeatedly executed, and step S
In 7, when it is determined that the minimum grid point interval is equal to or smaller than a predetermined value, it is estimated that each current source of the grid point group obtained in the final step S <b> 3 is a true current source.

<Simulation> A simulation was performed to confirm the effectiveness of the above method. Here, the virtual vector measurement pickup coil shown in FIG. 2 was set. The magnetic field generated by the same current source was obtained by calculation using this and the pickup coil for measuring only the radial component shown in FIG. At this time, in order to evaluate both of them equally, the number of measurement channels and the measurement area were set to be substantially equal. The vector measurement channel is 13 × 3 39 channels with a coil pitch of 37.5 mm, the radial measurement is 37 channels with a coil pitch of 25 mm, and the axis of each coil faces the center of the sphere on a 117 mm radius sphere. Was placed. However,
Since the tangential component of the magnetic field is affected by the volume current, the magnetic field generated by the current source is calculated using a spherical model and the effect of the volume current is considered (J. Sarvas, Phys. Med. Biol., Vol. Three
2, pp11-22, 1987).

An estimation simulation was performed on each of the magnetic field data measured in the vector direction and the radial direction by using the equation (9). Assuming that the head is a sphere having a radius of 80 mm, the magnetic sensors are arranged symmetrically about the Z axis (FIG. 12).
(A)). The distance from the surface of the sphere to the sensor is 37m
m. The current source has two current dipoles of position [mm] moment [nAm] (20, 0, 50) (0, 10, 0) (-20, 0, 5) (0, 10, 0). Was.

FIG. 3 shows the estimation results. FIG. 9A shows the estimation result of the current source based on the magnetic field data measured by the vector.
FIG. 7B shows an estimation result based on the measurement in the radial direction. In the figure, the circles indicate the set positions of the current sources, and the arrows indicate the estimated current sources. As is apparent from FIG. 3, according to the embodiment method of estimating the current source by applying the above-described equation (9) to the vector-measured magnetic field data, the current source is correctly estimated and measured in the radial direction. Equation for the magnetic field data
When (9) is applied, the current source is not correctly estimated.

Therefore, according to the present embodiment, of the parameters α, β, and γ in the above-described lattice point movement minimum norm method, only the movement parameter α in equation (8) may be set empirically. Since there is no need to set β and γ, the current source can be easily and accurately estimated.

<Automatic Adjustment of Movement Parameter α> Next, a method of automatically adjusting the movement parameter α that needs to be set in the above-described step S6 without depending on empirical settings will be described.

Depending on the value set for the movement parameter α, the estimation result may be completely different. If this value can be determined by any method, it is possible to perform highly general estimation that does not require empirical parameters, together with the method of the above-described embodiment.

Here, as a criterion for determining the movement parameter α, attention is paid to the norm of the solution obtained by the minimum norm method. Since the minimum norm solution is obtained by moving the grid points in each iteration in this method, the norm of the solution changes every time. Therefore, estimation was performed by setting various values for the movement parameter α, and the state of change in the norm of the solution was examined. As the sensor, the vector measurement pickup coil shown in FIG. 2 was used. The arrangement of the current source and each sensor was the same as in the above-described embodiment. FIG. 4 shows changes in the norm when α is 0.3 and 0.5. The horizontal axis in FIG. 4 is the number of repetitions, and the vertical axis is the norm of the solution. FIG. 5 shows the estimation results. When α is 0.3, the norm of the solution diverges as shown in FIG. 4A, resulting in a different estimation result as shown in FIG. 5A. On the other hand, when α is 0.5, the norm of the solution converges as shown in FIG. 4B, and a correct estimation result is obtained as shown in FIG. 5B.

From this, in each iteration, a grid point moving parameter α that minimizes the norm of the solution is obtained, and by moving each grid point using this parameter, the optimum moving parameter α is determined. It turns out to be good.

Hereinafter, the processing procedure of the current source estimating method using the automatic adjustment of the movement parameter α will be described with reference to the flowchart shown in FIG. Steps N1 to N4 in FIG.
Are steps S1 to S4 in the flowchart shown in FIG.
The description is omitted here.

In step N5, in the next step N6,
Before the grouping of the grid point group by using the above equation (8), the movement parameter α is optimized using the evaluation function f expressed by the following equation (10).

[0055]

(Equation 5)

In the equation (10), VP _j (α) is a solution obtained by moving the lattice points using the movement parameter α and obtained by the minimum norm method. Therefore, the evaluation function f is the norm of the solution. is there. N represents the number of grid points.

In steps N5 to N7, several parameters α ₁ , α ₂ , α ₃ ,.
By temporarily moving the grid points using these parameters, the respective minimum norm solutions are obtained. Then, these minimum norm solutions are given to equation (10), and the evaluation functions f (α ₁ ), f
The values of (α ₂ ), f (α ₃ ),... Are determined, and the parameter having the minimum value is adopted as the movement parameter α.
Accordingly, the minimum norm solution obtained by moving the lattice point based on the adopted movement parameter α is adopted, and the minimum norm solution based on other parameters is discarded.

Then, in step N8, the norm of the solution (value f _L-1 of the evaluation function) obtained by the previous processing of steps N4 to N7 and the norm of the current solution (value f _{L of the} evaluation function) Is obtained. If the amount of change Δf of the norm of this solution is equal to or less than a predetermined value,
If not, the process returns to step N4 to repeatedly execute the processes of steps N4 to N7 until the change amount Δf of the norm of the solution becomes equal to or less than a predetermined value.

According to the method shown in FIG. 6, not only the empirical parameters α, β, and γ are not required, but also the norm of the minimum norm solution is used as a condition for stopping the repetitive processing (step N8). The current source estimation process can be stopped at an appropriate number of repetitions.

<Simulation> A simulation was performed to confirm the effectiveness of the technique for automatically adjusting the movement parameter α. As the pickup coil, the vector measurement coil shown in FIG. 2 was set at 19 points on the spherical surface. Therefore, the number of channels is set to 57 channels of 19 × 3.
This was set on a spherical surface with a coil pitch of 25 mm and a radius of 131 mm. The head was a sphere with a radius of 80 mm, and the calculation of the magnetic field was performed in consideration of the effect of the volume current. Sensor is Z
They were arranged symmetrically about the axis, and the distance from the sphere on the head to the sensor was 36 mm. The current source set multiple current dipoles.

Assuming the cerebral cortex in the head sphere, three current dipoles were set on it. The position and moment of each current dipole are as follows. Position [mm] Moment [nAm] (-27.08, 4.78, 47.63) (-8.53, 1.50, -5.00) (-27.08, -4.78, 47.63) (-8.53, -1.50, -5.00) (4.91, -56.08, 32.50) (0.44, -4.98, -8.66)

FIG. 7 shows the result of current source estimation by the grid point moving minimum norm method while automatically adjusting the moving parameter α.
Shown in As shown in the figure, the current source is estimated near the correct position as set. When current source estimation is performed by this method, a solution can be obtained as a current dipole distribution even if the true current source is a single current dipole, but when the estimated current dipole moment is integrated, The moment value of the set current dipole was almost the same, confirming the effectiveness of this method.

[0063]

As is apparent from the above description, according to the present invention, the three orthogonal components of the magnetic field generated by the biological activity current are simultaneously detected by a plurality of magnetic sensors, so that the lattice point shift is achieved. In the minimum norm method, the accuracy of the existence of a current source at each grid point can be obtained by considering only the size of the current source at each grid point, and the density of the current sources near each grid point is considered. No need. Therefore, there is no need to empirically set a parameter that defines the degree to which the density of the current sources near each grid point affects the accuracy with which the current source exists at each grid point.
The current source can be easily and accurately estimated.

[Brief description of the drawings]

FIG. 1 is a flowchart of an embodiment.

FIG. 2 is a schematic diagram of a vector measurement pickup coil.

FIG. 3 is a diagram showing an estimation result by simulation.

FIG. 4 is a diagram illustrating a change in a norm of a solution according to a value of a movement parameter.

FIG. 5 is a diagram illustrating a result of a simulation according to a value of a movement parameter.

FIG. 6 is a flowchart of a process using automatic adjustment of a movement parameter.

FIG. 7 is a diagram showing a result of a simulation of the processing of FIG. 6;

FIG. 8 is an explanatory diagram of a conventional minimum norm method.

FIG. 9 is an explanatory diagram of grid point grouping in the grid point moving minimum norm method.

FIG. 10 is a diagram showing a state where a grid point is divided and moved.

FIG. 11 is a diagram illustrating a state where a grid point is further divided and moved.

FIG. 12 is a diagram showing an arrangement of a general magnetic sensor and its configuration.

[Explanation of symbols]

1 ... Multichannel SQID sensor S ₁ to S _m ... magnetic sensor N ... first grid point group N ₁ to N ₇ ... splitting grating point group _{L X, L Y, L Z} ... vector measurement pickup coil

──────────────────────────────────────────────────続 き Continued on front page (58) Field surveyed (Int.Cl. ⁷ , DB name) A61B 5/05

Claims (1)

(57) [Claims] 1. A method for estimating a physical quantity including any one of a position, a size, and a direction of a biological activity current source from data obtained by detecting a magnetic field generated by a biological activity current with a plurality of magnetic sensors. The grid points are set, and the relational expression between the unknown current source on each grid point and the magnetic field data measured by each magnetic sensor is minimized to minimize the norm of the vector having the current source at each grid point as an element. In the biological activity current source estimating method using a method (minimum norm method) for obtaining a physical quantity of each current source by adding a condition that the current condition is added, (a) setting a large number of grid points in the subject, The relational expression between the unknown current source on each grid point and the orthogonal three-direction magnetic field data obtained by simultaneously detecting the orthogonal three-direction components of the magnetic field generated by the biological activity current with a plurality of magnetic sensors is given by The said A first step of solving for a current source on each grid point by solving with the small norm method; and (b) each grid point according to the magnitude (intensity) of the current source at each grid point obtained in the first step. A second step of determining the accuracy of the presence of the current source in
(C) a third step of dividing the grid point group into a plurality of groups based on the accuracy obtained in the second step;
(D) a fourth step of relocating the grid point group by moving another grid point near the grid point where the current source having the maximum size exists in each of the divided grid point groups;
(E) a fifth step of obtaining a current source on each of the rearranged grid points by using the minimum norm method.